All Questions
214,294
questions
5
votes
2
answers
1k
views
raw data stationary but still can see trend and seaonality is stl
So I am looking at unit sales data. I am doing a univariate time series analysis. My data is weekly sales numbers figures, spanning 2012- 2014 (obviously no till end 2014). I first ploted my response ...
2
votes
1
answer
437
views
Complex level 1 variance mixed effects models in R
Take this mixed effects model in R:
$y_i = \beta_0 + \beta_1X_{ij} + u_{j} + e_{ij}$
where $u$ is a random effect (level 2 residual) with groups $j$. It is possible to allow the variance of $e_{ij}$ ...
0
votes
1
answer
254
views
Which distribution to choose when modeling variance of a normal distribution?
I have a simple time series model where there is a single hidden variable $\lambda_t$ which changes over time: $\lambda_{t+1} \sim \mathcal{N}(\lambda_t,\sigma)$. The $\lambda_t$ is then used as a ...
1
vote
1
answer
98
views
How should I inteprete this anova result?
I sas this example in the book R in action, the codes in R are as follows:
...
2
votes
5
answers
331
views
Thoughts on Mathematics of Statistics by Kenney? [closed]
This book is written in 1939. It's available here on archive.org.
Would you recommend this as an introduction to the mathematics of statistics for beginners?
5
votes
1
answer
8k
views
Find the mode of a probability distribution function
I am trying the find mode of a probability distribution function given by
\begin{equation}
g(x/\alpha,\beta,\sigma)=\frac{1}{\Gamma \left( \alpha \right)\beta^{\alpha}}exp\left\{{-\frac{x^2}{2\sigma^{...
3
votes
2
answers
16k
views
SVM and SMO main differences
I am unable to clearly see the main differences between SVM & SMO. While I get the fact that SMO provides better algorithm for QP solvers but I see that when I use this in Weka on my MacBook it ...
0
votes
0
answers
81
views
can individuals resampled in reoccurring cross section surveys be considered as panel dataset?
I have data from a reoccurring cross sectional firm survey, For every year a new sample was selected ( with replacement between years). The data is identified, so I can see the subset of firms appear ...
2
votes
1
answer
130
views
Confidence interval for a multiple of regression coefficient
I am trying to model relationship between length of stay of patients in hospital(Y) vs Age in years(X). The data set I've got doesn't specify the unit of length of stay.
So now estimated value of my ...
7
votes
1
answer
4k
views
Maximum Likelihood Estimation of Dirichlet Mean
Consider the problem of computing a Maximum-Likelihood estimate of the parameters to a finite Dirichlet distribution, given a set of multinomial observations (probability vectors) assumed to have been ...
1
vote
0
answers
443
views
What are the implications of using aggregated data in lme4 for GLMMs?
I'm working with the lme4 package in R, looking to fit GLMM models. For the proprietary data I'm working with, my dataset can ...
2
votes
0
answers
131
views
Variable effect in Weibull and Cox models
Is it possible to compare effect of variable on the survival time in the Cox model and in the Weibull regression model?
1
vote
1
answer
5k
views
How do you estimate $\alpha$ parameter of a latent dirichlet allocation model?
Blei has shown that it is possible to estimate $\alpha$ in a LDA model, but I have yet to find a library (any library; C, C++, Java, ...) to do so. Usually, implementations (including Blei's) treat $\...
4
votes
2
answers
6k
views
Single EM imputation with R (using Amelia or other packages)
I am trying to impute missing values with R. I would like to use the EM algorithm for that.
As it seems this algorithm is implemented in the ...
2
votes
2
answers
2k
views
Issues with using glmnet package for MATLAB [closed]
I am trying to use the glmnet MATLAB package to train my elastic net model on some huge data. My features are of size 13200, and I have around 6000 samples of these....
2
votes
1
answer
432
views
How can I plot this graph in R? [closed]
I'm reading "An Introduction to Statistical Learning" and noticed the following plot made in the book for a regression tree:
I'm trying to make a similar plot for my dataset but can't figure out how ...
2
votes
0
answers
39
views
Solving for primary variables of a linear program after already having solved for the dual
I was wondering if there is a general procedure of solving for the primary variables of a linear or quadratic or, in general, a convex program after already having solved the dual program.
The ...
3
votes
1
answer
252
views
Gamma GLM predicting the second parameter of the Gamma
The gamma distribution has two parameters, I understand that the linear predictor predicts $\mu = g^{-1}(X\beta)$ where $g$ is the link function but how does the linear predictor specify the second ...
2
votes
2
answers
184
views
If I ran 10+ unpaired t-tests, do I report them all?
1) Should I be reporting the results of all the t-tests I ran, or can I just talk about the ones that were significant?
2) Must I report the t-statistic, df, effect size in all cases?
I am pressed ...
34
votes
2
answers
16k
views
What is the distribution of $R^2$ in linear regression under the null hypothesis? Why is its mode not at zero when $k>3$?
What is the distribution of the coefficient of determination, or R squared, $R^2$, in linear univariate multiple regression under the null hypothesis $H_0:\beta=0$?
How does it depend on the number ...
3
votes
1
answer
282
views
Applications of bayesian inference to external ballistics?
I'm reading "The theory that would not die" by Sharon Bertsch McGrayne (Fine book. Strongly recommended to everyone). The author says that bayesian inference has been used for ballistics applications ...
1
vote
1
answer
4k
views
Partial least squares regression for categorical factor in R
I adjust the partial least squares regression for one categorical factor (2 levels – be or nottobe) with with the ...
5
votes
2
answers
9k
views
Use of bootstrap in clustering algorithms
Are there clustering algorithms that take advantage of bootstrap?
For example can one combine bootstrap with a standard K-Means algorithm to scale K-Means.
I was thinking if the following at a high-...
-2
votes
2
answers
493
views
The distribution of Gaussian density at a fixed point given random mean
Let's say I have random variable $\mu \sim N(0, \xi^2)$. Is there anything useful known about the distribution of random variable $d = N(x ; \mu, \sigma^2)$, that is, the distribution of the normal ...
1
vote
1
answer
177
views
Does standard deviation and its confidence interval consider the stochastic variability of data?
If we compute the standard deviation of a data set composed of a single feature and then compute its confidence interval, then can we say that these computations have considered the stochastic ...
2
votes
1
answer
2k
views
How do you set your own intercept in SPSS? [duplicate]
I am trying to specify the constant in a regression model using SPSS. Does anyone have an idea on how to do this?
3
votes
1
answer
3k
views
Relation between the tuning parameter $\lambda$, parameter estimates $\beta_i$ and constraint $s$ in LASSO logistic regression
In the context of LASSO logistic regression, I understand that $\lambda$ is the tuning parameter obtained by cross validation. There is also the constraint parameter $s$ ($\sum_{i=1}^p|\hat\beta_i|\le ...
0
votes
0
answers
29
views
Cross correlation using photographic film
I used to work for a guy who told me about working for an oil company, probably in the 1960's, doing cross correlation work by sliding two pieces of developed film strips across each other (maybe they ...
2
votes
1
answer
7k
views
step {stats} is too slow. Are there multicore solutions?
I am finding that trying to do a stepwise logistic regression is far too slow on my data set (6 hours). Is anyone aware of any faster solutions out there? Perhaps one that takes advantage of the ...
6
votes
3
answers
4k
views
Creating univariable smoothed scatterplot on logit scale using R
I am learning logistic regression modeling from the book Applied Logistic Regression by Hosmer.
I need to create a plot named "create univariable smoothed scatterplot on logit scale", ...
7
votes
1
answer
601
views
Does the log likelihood become unimodal when the sample size goes to infinity?
I know that, under the usual regularity conditions, the MLE converges to the true parameter values as the sample size gets large. And the scaled MLE tends to being normally distributed. However, in a ...
1
vote
2
answers
293
views
Is there any way I can manually set the intercept in SPSS?
As part of my dissertation I am looking into the relationship between temperature and methane emissions. A large proportion of this work relies on statistical interpretation and analysis. When ...
3
votes
1
answer
3k
views
Odds ratio in logistic regression with multiple predictors
It seems to be commonly accepted that $e^\beta$ corresponds to the OR in logistic regressions. Although I understand that in the univariate case this definitely seems to correspond, i.e.
$$
OR = \...
5
votes
3
answers
3k
views
$R^2$ of linear regression with no variation in the response variable
Suppose I wish to fit $\hat{y} = \beta_0 + \beta_1x$ where the the data is as follows:
x = 0.0, 0.1, 0.2, 0.3, 0.4
y = 0.0, 0.0, 0.0, 0.0, 0.0
Clearly, $\hat{\...
3
votes
1
answer
29k
views
Simple Analysis of Likert Result with Mode and Median
So I made a questionnaire using Likert Scale. Let's say that I want to know "user's satisfaction of new web interface", where I used 5 questions with Likert Scale to answer that one question. The ...
1
vote
0
answers
625
views
If peak was higher than normal, why does updated arima model overestimate activity in remaining time series?
I have a number of time series with strong seasonality and I am using auto.arima() from R's Forecast package along with Fourier and dummy/explanatory variables to address the seasonality to make ...
1
vote
1
answer
259
views
Terminology Numerator Baye's Rule?
I am considering this formulation of Baye's Rule
$\mathrm{Pr}(\theta | D) = \frac {\mathrm{Pr}(\theta)\mathrm{Pr}(D|\theta)}{\int \mathrm{Pr}(D|\theta)\mathrm{Pr}(\theta)\mathrm{d}\theta}$
Is there ...
1
vote
1
answer
235
views
Obtain adjusted means - Weight? Standardize? Use LSmeans?
I'm attempting to compare means from one year to another (and between groups at the same time point) by calculating adjusted values.
I'm not sure what method to use. I've thought about the following:
...
1
vote
0
answers
119
views
The probability that a process signals (simple conditional probability)
I have this problem (from Montgomery's Applied Probability and Statistics, 5th Edition, problem 2-145, if anyone wants to see the original problem) but it's long, so for the sake of brevity I'll give ...
2
votes
0
answers
125
views
Response Functions in a Random Forest
I am reading a chapter about random forest in a textbook. After the section about the predictor importance, the author introduces "Response Functions" as follow:
"Predictor importance is only part of ...
2
votes
1
answer
2k
views
sklearn.tree.export_graphviz values do not add up to samples
When I run tree.export_graphviz() after training a sklearn.ensemble.RandomForestClassifier() on my data, I get some leaf nodes where the samples count doesn't match the value array, like this:
...
2
votes
1
answer
1k
views
Sampling distribution, mean, standard deviation of finite discrete uniform population
Given positive integers $a$ and $b$ ($b \leq a$),
where $c$ is the set of all combinations of $a$ digit binary numbers, with $b$ 1's,
and where $c_1$ is least significant bit, and $c_a$ is most ...
7
votes
1
answer
8k
views
generate a time series comprising seasonal, trend and remainder components in R
I want to generate a time series comprising three components: a seasonal component, a trend component and a remainder component. Moreover, I want to be able to chnage the level of trend, seasonality ...
15
votes
4
answers
803
views
Good practice for statistical analysis in a business environment
(While I realise this isn't strictly about statistics, it is about the dissemination of statistics in a business environment so I have assumed it is still within the topic range of CV)
A brief bit of ...
5
votes
1
answer
74
views
Method/workflow for analyzing data with changing structure?
I am analyzing data relating to networks that evolve over times (more precisely, a snap shot of the network at every discrete time step). Each node of the network denotes a person who perform some ...
2
votes
1
answer
2k
views
Maximum of uniformly distributed random variables using iterated expectations
I'm working through the problems in Wasserman's 'All of Statistics'. The chapter on expectations and conditional expectations ends with a (seemingly) easy problem:
Let $Y$ be the maximum of $n$ iid ...
2
votes
0
answers
75
views
Estimating dynamic panel model with tricky survey data
I have a theoretical model that (given my ideal data set) could be taken to the data with a dynamic panel regression of the following form:
$s_{i,t} = \eta_i + \alpha a_{i,t} + \beta b_{i,t} + \...
9
votes
2
answers
906
views
Distributions on subsets of $\{1, 2, ..., J\}$?
I'm wondering if there are any sorts of standard distributions on subsets of integers $\{1, 2, ..., J\}$. Equivalently, we could express this as a distribution on a $J$ length vector of binary ...
2
votes
0
answers
60
views
Split thirds correlation
You hear about split-half correlations often as a measure of reliability. But is there a reason that split-third correlations (or split-fourth, split-fifth, etc.) are never used? Shouldn't they ...
2
votes
1
answer
403
views
Proof of optimality of mean squared loss
Suppose I am building a predictor for $y = f_w(x) + noise$ using some framework with parameters $w$ (linear regression, neural networks, etc.) given a number of training examples $\{(x_i,y_i)\}$.
I ...